Interacting and making personalized recommendations of places of interest to tourists

Advances in Intelligent Systems and Computing, 353Nowadays, applications that are developed to support tourists should go much further than simply providing information about places or recommending places or routes based on the user location. They should be able to provide users with simple mechanisms to interact with places of interest and provide them with relevant information and recommendations about new relevant places of interest or tours according to their preferences and the preferences of other tourists with similar interests. In this work we describe a system that explores information about tourists’ interactions with places of interest and their opinions about each place, to recommend new places of interest, pedestrian tours and to promote products and services which are in accordance with their expectations. First experiments show that the system can help the tourists to interact with places of interest, helping them in their visits and also to promote shops and services

Exploring attributes, sequences, and time in Recommender Systems: From classical to Point-of-Interest recommendation

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingenieria Informática. Fecha de lectura: 08-07-2021Since the emergence of the Internet and the spread of digital communications throughout the world, the amount of data stored on the Web has been growing exponentially. In this new digital era, a large number of companies have emerged with the purpose of ltering the information available on the web and provide users with interesting items. The algorithms and models used to recommend these items are called Recommender Systems. These systems are applied to a large number of domains, from music, books, or movies to dating or Point-of-Interest (POI), which is an increasingly popular domain where users receive recommendations of di erent places when they arrive to a city. In this thesis, we focus on exploiting the use of contextual information, especially temporal and sequential data, and apply it in novel ways in both traditional and Point-of-Interest recommendation. We believe that this type of information can be used not only for creating new recommendation models but also for developing new metrics for analyzing the quality of these recommendations. In one of our rst contributions we propose di erent metrics, some of them derived from previously existing frameworks, using this contextual information. Besides, we also propose an intuitive algorithm that is able to provide recommendations to a target user by exploiting the last common interactions with other similar users of the system. At the same time, we conduct a comprehensive review of the algorithms that have been proposed in the area of POI recommendation between 2011 and 2019, identifying the common characteristics and methodologies used. Once this classi cation of the algorithms proposed to date is completed, we design a mechanism to recommend complete routes (not only independent POIs) to users, making use of reranking techniques. In addition, due to the great di culty of making recommendations in the POI domain, we propose the use of data aggregation techniques to use information from di erent cities to generate POI recommendations in a given target city. In the experimental work we present our approaches on di erent datasets belonging to both classical and POI recommendation. The results obtained in these experiments con rm the usefulness of our recommendation proposals, in terms of ranking accuracy and other dimensions like novelty, diversity, and coverage, and the appropriateness of our metrics for analyzing temporal information and biases in the recommendations producedDesde la aparici on de Internet y la difusi on de las redes de comunicaciones en todo el mundo, la cantidad de datos almacenados en la red ha crecido exponencialmente. En esta nueva era digital, han surgido un gran n umero de empresas con el objetivo de ltrar la informaci on disponible en la red y ofrecer a los usuarios art culos interesantes. Los algoritmos y modelos utilizados para recomendar estos art culos reciben el nombre de Sistemas de Recomendaci on. Estos sistemas se aplican a un gran n umero de dominios, desde m usica, libros o pel culas hasta las citas o los Puntos de Inter es (POIs, en ingl es), un dominio cada vez m as popular en el que los usuarios reciben recomendaciones de diferentes lugares cuando llegan a una ciudad. En esta tesis, nos centramos en explotar el uso de la informaci on contextual, especialmente los datos temporales y secuenciales, y aplicarla de forma novedosa tanto en la recomendaci on cl asica como en la recomendaci on de POIs. Creemos que este tipo de informaci on puede utilizarse no s olo para crear nuevos modelos de recomendaci on, sino tambi en para desarrollar nuevas m etricas para analizar la calidad de estas recomendaciones. En una de nuestras primeras contribuciones proponemos diferentes m etricas, algunas derivadas de formulaciones previamente existentes, utilizando esta informaci on contextual. Adem as, proponemos un algoritmo intuitivo que es capaz de proporcionar recomendaciones a un usuario objetivo explotando las ultimas interacciones comunes con otros usuarios similares del sistema. Al mismo tiempo, realizamos una revisi on exhaustiva de los algoritmos que se han propuesto en el a mbito de la recomendaci o n de POIs entre 2011 y 2019, identi cando las caracter sticas comunes y las metodolog as utilizadas. Una vez realizada esta clasi caci on de los algoritmos propuestos hasta la fecha, dise~namos un mecanismo para recomendar rutas completas (no s olo POIs independientes) a los usuarios, haciendo uso de t ecnicas de reranking. Adem as, debido a la gran di cultad de realizar recomendaciones en el ambito de los POIs, proponemos el uso de t ecnicas de agregaci on de datos para utilizar la informaci on de diferentes ciudades y generar recomendaciones de POIs en una determinada ciudad objetivo. En el trabajo experimental presentamos nuestros m etodos en diferentes conjuntos de datos tanto de recomendaci on cl asica como de POIs. Los resultados obtenidos en estos experimentos con rman la utilidad de nuestras propuestas de recomendaci on en t erminos de precisi on de ranking y de otras dimensiones como la novedad, la diversidad y la cobertura, y c omo de apropiadas son nuestras m etricas para analizar la informaci on temporal y los sesgos en las recomendaciones producida

Not all trips are equal: Analyzing foursquare check-ins of trips and city visitors

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ

РАЗРАБОТКА СИСТЕМЫ ЦЕЛЕВЫХ ПОКАЗАТЕЛЕЙ ВНЕДРЕНИЯ КОНЦЕПЦИИ СОПРОИЗВОДСТВА В МАРКЕТИНГЕ ТЕРРИТОРИЙ

The article deals with theoretical aspects of the development and implementation of the system of target indicators of the co-production concept in the marketing of territories. The main stages and elements on which the presented system should be based are described. These include: analysis of target markets, analysis of existing and potential types of co-production (volunteering, crowdsourcing, creation of a positive information field, couchsurfing, non-professional excursions and crowdfunding), analysis and systematization of strategic goals for marketing of territories, determining the system of target indicators of co-production, determining the values of target co-production indicators, and development of an algorithm for implementing the suggetsed system of target indicators. Also, the article presents an algorithm for the formation and implementation of the proposed system of target indicators of co-production in the marketing of territories. The algorithm consists of the following four stages: analysis of the existing complex of territory marketing; assessment of the residents’ readiness to support marketing activities in the field of tourism aimed at promoting the territories; implementation of an improved marketing complex, and analysis of the results of implemented activities on co-production in the marketing of territories in the tourism industry. This algorithm can be used by producers of public goods of different levels when planning and implementing marketing activities related to the promotion of territories.В статье рассматриваются теоретические аспекты разработки и внедрения системы целевых показателей концепции сопроизводства в маркетинге территорий. Описаны основные этапы и элементы, на которых должна основываться представленная система. К ним относятся: анализ целевых рынков, анализ существующих и потенциальных типов сопроизводства (волонтёрство, краудсорсинг, создание позитивного информационного поля, каучсёрфинг, непрофессиональные экскурсии и краудфандинг), анализ и систематизация стратегических целей маркетинга территорий, определение системы целевых показателей сопроизводства, определение значений целевых показателей сопроизводства и разработка алгоритма внедрения системы целевых показателей. Также в статье представлен алгоритм формирования и внедрения предложенной системы целевых показателей сопроизводства в маркетинге территорий. Алгоритм состоит из следующих четырех этапов: анализ существующего комплекса маркетинга территории; оценка готовности жителей поддерживать маркетинговые мероприятия в сфере туризма, направленные на продвижение территорий; реализация усовершенствованного комплекса маркетинга и анализ результатов реализованных мероприятий по сопроизводству в маркетинге территорий в сфере туризма. Данный алгоритм может быть использован производителями общественных благ разного уровня при планировании и реализации маркетинговой деятельности, связанной с продвижением территорий

Sustainability Initiatives in East Bayside Neighborhood Portland, Maine

This is a bundle containing research on sustainability initiatives that could be implemented in the East Bayside neighborhood of Portland, ME. These six essays were prepared by the Spring, 2010 Sustainable Communities Class known as CPD 602 at the University of Southern Maine. The class is part of the core curriculum of the Community Planning and Development program of the Muskie School of Public Service at the university. The instructor for the class was Samuel Merrill, Ph. D. who is also director of the New England Environmental Finance Center at the University. These papers were prepared in conjunction with Alan Holt, an architect and instructor at USM who coordinated work being done in the East Bayside neighborhood by a Sustainable Design Assessment Team (SDAT) funded by the American Institute of Architects (AIA). This work is an academic exercise, and while some aspects of these recommendations may be implemented please note that this is not an official planning document. Rather, these ideas merit public scrutiny and the full democratic public participation process before they can proceed further

People, place, enterprise: proceedings of the first annual conference on Olympic Legacy 8 and 9 May 2008

The Olympic Legacy: People, Place, Enterprise conference took place at the University of Greenwich in May 2008. The first in a series of annual conferences, it brought together leading academics, policy makers and practitioners to debate the lasting legacy of the games. The conference had four themes: social and cultural regeneration; Olympic tourism; enterprise, including social enterprise and skills development, and education, providing a multi-dimensional perspective on the likely impacts of the forthcoming London Olympics